Optical character recognition ("OCR") systems are used in many industrial applications. In semiconductor manufacturing processes, OCR is used to read laser-etched serial numbers on wafers at many stages of the process, such as during test and assembly steps. In a typical wafer reading application, a machine-vision vision system is directly integrated with a piece of process equipment, such as a wafer handler or sorter, or is positioned at a dedicated reading station. In either case, the vision system uses an imaging device to capture an image of each semiconductor wafer. The vision system then compares each character in the wafer serial number to a pretrained font stored in memory. The character is identified when a match in memory is located.
Size differences between the image of the characters and the pretrained fonts often hamper proper identification of the characters. More particularly, the pretrained fonts stored in memory form a template. Typically, the template is a matrix of pixels. Each of the characters of the image are also represented as a matrix of pixels. When the template is compared with the character in the image, each pixel of the image is compared with each pixel of the template. The character can only match the template if the character size in the image of the wafer and the character size of the template are substantially the same. When the size of the character in the image and the size of the pretrained font differ, no match is found, and, therefore, the character is not identified.
To correct the problem, typically the image of the wafer is scaled so that it will match the appropriate template. The machine-vision vision system determines the size of the characters in the image of the wafer as a percentage of the size of the characters stored in memory by using calibration data obtained during set-up, such as magnification. The vision system then scales the stored font so that it can accurately identify the characters at run-time.
The OCR calibration step typically requires an operator to describe how the source images are distorted. Commonly, the operator describes the source image by entering numeric values of angles and coordinates using a keyboard. When the area that needs to be characterized by the user is irregular, such as a polar region on a wafer, it becomes intuitively difficult for the operator to guess an arc that fits the area.